Reeves, Todd D.
M.S. (Master of Science)
Department of Educational Technology, Research and Assessment (ETRA)
An expanding culture of accountability in education has led to an influx in the amount and types of data teachers are expected to collect and use to increase student achievement. Research has identified data-driven decision making (DDDM) as a way for teachers to use educational data to promote more effective instruction and ultimately, to better student outcomes. Despite available data and research that supports the use of DDDM, using it to make instructional decisions is still a struggle for teachers. Therefore, this study looks at the relationship between DDDM-related coursework and teacher self-efficacy and anxiety for DDDM. In theory, DDDM-related coursework learning opportunities should provide teachers increased mastery experiences and in turn, greater self-efficacy for DDDM and lower anxiety about the practice.
In order to investigate, this study used a secondary analysis of existing data to examine the extent to which teachers are taking DDDM-related courses, and relationships among the types of these courses taken by teachers and their DDDM self-efficacy and DDDM anxiety. Descriptive statistics and multiple regression analyses were conducted on each of two merged datasets (pre-service and in-service). Results from this study suggest that most pre-service and in-service teachers are taking DDDM-related courses and that some of these courses are associated with higher DDDM self-efficacy and lower DDDM anxiety in teachers. Findings contribute new evidence for connections between course-related learning opportunities and teacher self-efficacy beliefs.
Hamilton, Valerie M., "Course Taking and Teacher Data-Driven Decision Making Self-Efficacy and Anxiety: A Secondary Analysis" (2019). Graduate Research Theses & Dissertations. 7089.
Northern Illinois University
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